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Knowledge Bases

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Structure-based knowledge acquisition from electronic lab notebooks for research data provenance documentation.

Journal of biomedical semantics
BACKGROUND: Electronic Laboratory Notebooks (ELNs) are used to document experiments and investigations in the wet-lab. Protocols in ELNs contain a detailed description of the conducted steps including the necessary information to understand the proce...

TextRank Keyword Extraction Algorithm Using Word Vector Clustering Based on Rough Data-Deduction.

Computational intelligence and neuroscience
When TextRank algorithm based on graph model constructs graph associative edges, the co-occurrence window rules only consider the relationships between local terms. Using the information in the document itself is limited. In order to solve the above ...

Combined strategy of knowledge-based rule selection and historical data percentile-based range determination to improve an autoverification system for clinical chemistry test results.

Journal of clinical laboratory analysis
BACKGROUND: Current autoverification, which is only knowledge-based, has low efficiency. Regular historical data analysis may improve autoverification range determination. We attempted to enhance autoverification by selecting autoverification rules b...

End-to-End provenance representation for the understandability and reproducibility of scientific experiments using a semantic approach.

Journal of biomedical semantics
BACKGROUND: The advancement of science and technologies play an immense role in the way scientific experiments are being conducted. Understanding how experiments are performed and how results are derived has become significantly more complex with the...

Document-level medical relation extraction via edge-oriented graph neural network based on document structure and external knowledge.

BMC medical informatics and decision making
OBJECTIVE: Relation extraction (RE) is a fundamental task of natural language processing, which always draws plenty of attention from researchers, especially RE at the document-level. We aim to explore an effective novel method for document-level med...

Relieving the Incompatibility of Network Representation and Classification for Long-Tailed Data Distribution.

Computational intelligence and neuroscience
In the real-world scenario, data often have a long-tailed distribution and training deep neural networks on such an imbalanced dataset has become a great challenge. The main problem caused by a long-tailed data distribution is that common classes wil...

MKA: A Scalable Medical Knowledge-Assisted Mechanism for Generative Models on Medical Conversation Tasks.

Computational and mathematical methods in medicine
Using natural language processing (NLP) technologies to develop medical chatbots makes the diagnosis of the patient more convenient and efficient, which is a typical application in healthcare AI. Because of its importance, lots of researches have com...

Metaknowledge Enhanced Open Domain Question Answering with Wiki Documents.

Sensors (Basel, Switzerland)
The commonly-used large-scale knowledge bases have been facing challenges in open domain question answering tasks which are caused by the loose knowledge association and weak structural logic of triplet-based knowledge. To find a way out of this dile...

The mining and construction of a knowledge base for gene-disease association in mitochondrial diseases.

Scientific reports
Mitochondrial diseases are a group of heterogeneous genetic metabolic diseases caused by mitochondrial DNA (mtDNA) or nuclear DNA (nDNA) gene mutations. Mining the gene-disease association of mitochondrial diseases is helpful for understanding the pa...

Enhancing unsupervised medical entity linking with multi-instance learning.

BMC medical informatics and decision making
BACKGROUND: A lot of medical mentions can be extracted from a huge amount of medical texts. In order to make use of these medical mentions, a prerequisite step is to link those medical mentions to a medical domain knowledge base (KB). This linkage of...